Sending reports of asset transport status

ABSTRACT

In some examples, a device includes a processor configured to compare a current transport status of the asset to a predicted transport status of the asset at each respective time instance of a plurality of time instances, and in response to determining that the current transport status does not differ from the predicted transport status by greater than a specified threshold, skip sending a report relating to the current transport status to a service over a network at the respective time instance of the plurality of time instances.

BACKGROUND

Trucks, tractor-trailers, or tractors that are connected to chassis forcarrying containers can be used to transport cargo that includes goods.Cargo can be transported from an origin (such as a factory, a warehouse,a retail outlet, etc.) to a destination (such as retail outlet, awarehouse, customer premises, etc.) along a route.

BRIEF DESCRIPTION OF THE DRAWINGS

Some implementations of the present disclosure are described withrespect to the following figures.

FIG. 1 is a block diagram of an example arrangement that includes anasset tracking device and a remote service, according to someimplementations.

FIGS. 2A and 2B are flow diagrams of example processes performed by anasset tracking device according to some implementations.

FIG. 3 illustrates an example of reporting or skipping the reporting ofcurrent status reports, according to some implementations.

FIG. 4 is a flow diagram of an example process performed by an assettracking device according to alternative implementations.

FIG. 5 illustrates a graphical user interface (GUI) visualizationshowing actual and predicted locations of an asset, according to someimplementations.

FIGS. 6 and 7 are message flow diagrams showing signaling between anasset tracking device and a service, according to furtherimplementations.

FIG. 8 is a block diagram of an example system according to someimplementations.

DETAILED DESCRIPTION

In the present disclosure, use of the term “a,” “an”, or “the” isintended to include the plural forms as well, unless the context clearlyindicates otherwise. Also, the term “includes,” “including,”“comprises,” “comprising,” “have,” or “having” when used in thisdisclosure specifies the presence of the stated elements, but do notpreclude the presence or addition of other elements.

A moveable platform can be used to carry physical items (also referredto as “assets”) between different geographic locations. For example, themoveable platform can be a container (that is attached to a tractor), atruck, or a trailer, where the container provides an enclosed space inwhich the physical items can be stored during shipment. In otherexamples, the moveable platform can include another type of carrierstructure that is able to carry physical items. More generally, themoveable platform can be part of, mounted on, or attached, asapplicable, to a vehicle, such as a truck, a trailer, a tractor, a car,a train, a ship, an airplane, and so forth.

An entity such as a shipper, a distributor, a manufacturer, a seller ofgoods, or any other entity may wish to track assets (such as cargo) thatare being transported using moveable platforms. To do so, an assettracking device can be mounted on a moveable platform. An asset trackingdevice refers to an electronic device that is able to perform trackingof a transport status as well as other information relating to an assetthat is carried by a moveable platform. The asset tracking device caninclude a sensor or multiple sensors to acquire certain sensorinformation. The transport status can include a current location of anasset that is being tracked by the asset tracking device, an estimated(expected) time of arrival of the asset that is tracked by the assettracking device, or any other information that relates to the transportof the asset.

A current location can include a global positioning system (GPS)location, a location derived based on triangulation of signals from basestations or other wireless access network nodes, or other types oflocation information. The current location changes as the asset is movedby a moveable platform.

An estimated time of arrival of an asset refers to a time that the assetis expected to arrive at a specified destination. During transport, theestimated time of arrival can change (increase or decrease), such as dueto unexpected delays, faster than expected travel times of a moveableplatform, or other factors.

Examples of other information that can be communicated by an assettracking device includes any or some combination of the following: aload status of a moveable platform (e.g., whether or not a moveableplatform is loaded with asset(s) or an amount of loading of the moveableplatform, e.g., 25% loaded, 50% loaded, etc.), conditions of theenvironment around the asset(s) (e.g., a measured temperature, ameasured humidity, etc.), or other information that can be acquired bysensor(s).

Each of multiple asset tracking devices on various moveable platformscan communicate a transport status and other sensor information over anetwork to a remote service to allow the remote service to track assetsthat are being moved by the moveable platforms. The remote service caninclude a server or a collection of servers and associated networkequipment that may be located at one fixed location or in a mobiledevice or as part of a data center or cloud. Alternatively, the remoteservice can include program code executed in a system, such as a cloudsystem or other type of system, that includes a computer or adistributed arrangement of computers. Asset tracking can involvetracking of any or some combination of the following: current locationsof the assets, estimated time of arrival of assets, cargo load status ofmoveable platforms, conditions of the environment around the assets(where such conditions can include a measured temperature, a measuredhumidity, etc.), and/or other information.

An asset tracking device can include a communication component tocommunicate over a network. In some examples, asset tracking devicesmounted on moveable platforms can be part of a larger network ofdevices. This larger network of devices can be part of the“Internet-of-Things” (IoT) technology paradigm to allow different typesof devices to communicate different types of data (including sensordata, voice data, video data, e-mail data, picture or image data,messaging data, web browsing data, and so forth). In addition to networktraffic communicated by computers, smartphones, wearable devices, andthe like, the IoT technology paradigm contemplates that other types ofdevices, including household appliances, vehicles, sensor devices,thermostats, and so forth, have connectivity to a network to allow thedevices to communicate respective data.

More generally, asset tracking using network connected asset trackingdevices can involve acquiring transport status information and/or sensorinformation, transmitting the transport status information and/or sensorinformation, and aggregating such transport status information and/orsensor information or producing other measures based on the transportstatus information and/or sensor information to determine informationassociated with the assets that are being transported by moveableplatforms. Based on data received from the asset tracking devices, aservice can update a database, run analytics, and/or present statusinformation for display, such that further decisions or actions can beperformed. The asset tracking can be used to improve fleet utilization,reduce operating cost, reduce loss of assets due to theft, and so forth.

An asset tracking device may be run using a battery that may have tolast a relatively long period of time (e.g., many years) withoutrecharge. As a result, it is desirable to reduce power consumption ofthe asset tracking device to the extent possible. In examples where thecommunication component of the asset tracking device is a cellular modemor other type of wireless transceiver, a significant amount of time canbe spent in the initial access of a cellular access network or othertype of wireless access network to gain wireless communication serviceto allow the asset tracking device to send a report to a remote service.

An example cellular access network can operate according to theLong-Term Evolution (LTE) standards as provided by the Third GenerationPartnership Project (3GPP). The LTE standards are also referred to asthe Evolved Universal Terrestrial Radio Access (E-UTRA) standards. Inother examples, other types of cellular access networks can be employed,such as second generation (2G) or third generation (3G) cellular accessnetworks, such as a Global System for Mobile (GSM) cellular accessnetwork, an Enhanced Data rates for GSM Evolution (EDGE) cellular accessnetwork, a Universal Terrestrial Radio Access Network (UTRAN), a CodeDivision Multiple Access (CDMA) 2000 cellular access network, and soforth. In further examples, cellular access networks can be fifthgeneration (5G) and beyond cellular access networks. In additionalexamples, a wireless access network can include a wireless local areanetwork (WLAN), which can operate according to the Institute ofElectrical and Electronic Engineers (IEEE) 802.11 or Wi-Fi AllianceSpecifications. In other examples, other types of wireless accessnetworks can be employed by asset tracking devices to communicate with aremote service, such as a Bluetooth link, a Zigbee network, and soforth.

In a cellular access network, the asset tracking device can performvarious operations to establish a connection with a cellular accessnetwork such that the asset tracking device can perform communicationsof application data (including transport status information and/or othersensor information) over the cellular access network. For example, theasset tracking device can perform a Received Signal Strength Indicator(RSSI) scan to measure a received signal strength in a frequency band ofinterest. The asset tracking device can then identify specific channelsof interest in which a received signal strength is above a predeterminedthreshold, and select those channels for further processing. In eachselected channel, the asset tracking device decodes synchronizationsignals to perform synchronization with identified cells of the cellularaccess network. The asset tracking device also reads certain systeminformation, and decodes such system information for each identifiedcell. The asset tracking device can then perform cell and public landmobile network (PLMN) selection to identify the best cell belonging to apreferred PLMN and camps on the cell. Upon selecting a suitable cell,the asset tracking device performs a random access procedure and anattach procedure. Subsequent to attaching to the network, the assettracking device can transmit and receive application data, such astransport status and/or sensor information.

The foregoing sequence of tasks to establish a connection between theasset tracking device and a cellular access network is both timeconsuming and can consume a large amount of power, particularly ifperformed multiple times to send multiple reports.

Establishing connections with other types of wireless networks cansimilarly be time consuming and can consume a relatively large amount ofpower at the asset tracking device.

In some examples, when performing asset tracking, an asset trackingdevice can send reports to a remote service over a network atpredetermined times. Such predetermined times can be periodic times,where the asset tracking device sends a report after each periodic timeinterval. In other examples, the asset tracking device can send reportsat other scheduled times. A “report” can refer to any collection ofinformation (send in one or more messages or one or more data units).

The periodicity of reports transmitted by the asset tracking device tothe remote service can be based on whether or not the moveable platformon which the asset tracking device is mounted is moving and can beconfigurable. For example, the asset tracking device can send reports asfrequently as every 15 minutes when the moveable platform is in motion.In other examples, such as when the moveable platform is not in motionor is moving slowly, the asset tracking device can send reports atlonger time intervals.

The asset tracking device can keep its wireless transceiver (e.g.,cellular modem or other type of wireless transceiver) off between thepredetermined times at which reports are sent, or alternatively, theasset tracking device can maintain the wireless transceiver on (but in alower power mode) between sending reports. In either case, there can besubstantial power consumption at the asset tracking device when sendingreports, which can deplete the battery of the asset tracking device inimplementations where the asset tracking device is battery-powered. Whenthe wireless transceiver is turned off between sending of reports, theasset tracking device has to go through a connection procedure toconnect to a wireless access network before a report can be sent. On theother hand, when the wireless transceiver is maintained in the on statebetween sending of reports, the wireless transceiver consumes power whensending reports even though the wireless transceiver may be in a lowerpower mode.

FIG. 1 is a block diagram of an example arrangement that includes amoveable platform 102 on which an asset tracking device 104 is mounted.Although not shown, the moveable platform 102 also carries an asset (ormultiple assets). The asset tracking device 104 includes a sensor 106and a communication transceiver 108 (such as a cellular modem or othertype of wireless transceiver). The communication transceiver 108includes a transmitter (to transmit data) and a receiver (to receivedata). Although just one sensor 106 is shown, it is noted that the assettracking device 104 can include multiple sensors, for acquiringrespective different information. In some examples, the sensor 106 caninclude a GPS receiver to acquire a GPS location of the asset trackingdevice 104. In other examples, the sensor 106 can derive a position ofthe asset tracking device 104 based on triangulation of signals receivedfrom wireless access network nodes (e.g., base stations of a cellularaccess network or access points of a WLAN).

The sensor(s) 106 can also acquire other information, such asenvironmental information (e.g., temperature, humidity, etc.),information of a speed of the moveable platform 102, a load status ofthe moveable platform, and so forth.

FIG. 1 also shows an access network 110, which can be a cellular accessnetwork, a WLAN, or another type of wireless access network. The accessnetwork 110 includes a wireless access network node 112, which can be acellular base station or other type of wireless access network node,such as an access point (AP) of a WLAN that operates according to theIEEE 802.11 standards. The access network 110 can include multiplewireless access network nodes 112.

As the moveable platform 102 moves between different locations, theasset tracking device 104 is able to communicate with different wirelessaccess network nodes or with different access networks.

The access network 110 is coupled to a service 114 that is to receiveand process asset tracking information transmitted by the asset trackingdevice 104. The service 114 can include one or more physical servers, orcan include program code executed on one or multiple computers.

The asset tracking device 104 includes a processor 105, which caninclude any or some combination of the following: a microprocessor, acore of a multi-core microprocessor, a microcontroller, a programmablegate array, a programmable integrated circuit device, or any otherhardware processing circuit.

The asset tracking device 104 also includes a battery 109 to providepower to various electronic components of the asset tracking device 104,such as the processor 105, the sensor 106, the communication transceiver108, and so forth.

As further shown in FIG. 1, a client device 116 can communicativelycouple to the service 114, to access information stored by the service114. The client device 116 can include any of the following: a desktopcomputer, a notebook computer, a tablet computer, a smart phone, awearable device (a smart watch, smart eyeglasses, a head-mounted device,etc.). A user can use the client device 116 to access status trackinginformation (reported by asset tracking devices) from the service 114,access results (e.g., reports, notifications, etc.) based on statustracking information reported by asset tracking devices, and so forth.

FIG. 2A is a flow diagram of a process that can be performed by an assettracking device, such as the asset tracking device 104. Morespecifically, the process of FIG. 2A can be performed by the processor105 in the asset tracking device 104. In some examples, machine-readableinstructions are executable on the processor 105 to perform the tasks ofFIG. 2A. In other examples, the processor 105 can be implementedentirely using hardware to perform the tasks of FIG. 2A.

According to FIG. 2A, it is assumed that the processor 105 is able tosend multiple reports of transport statuses of an asset at respectivetime instances (e.g., at periodic intervals or at non-periodic times).The transport status included in each report is the current transportstatus of the asset at the time that (or close in time to when) thereport was sent.

The processor 105 compares (at 202) a current (actual) transport statusto a predicted transport status of the asset at each respective timeinstance of multiple time instances. The “current transport status” canrefer to an updated transport status that is measured or derived by theprocessor 105 at a current respective time instance. The predictedtransport status can include a predicted location of the asset at aparticular time, or an estimated time of arrival of the asset, or anyother predicted information that relates to the transport of the asset.The predicted transport status can be computed by the asset trackingdevice 104, or alternatively, can be computed by the remote service 114and transmitted to the asset tracking device 104 by the service 114.

The processor 105 determines (at 204) whether the current transportstatus differs from the predicted transport status by greater than aspecified threshold. The specified threshold can be a thresholdstatically or dynamically set by the asset tracking device 104, or thatis received by the asset tracking device 104 from the remote service114. By doing this, the processor 105 determines whether the predictedtransport status is accurate or not. In other words, if the predictedtransport status differs from the current transport status by greaterthan the specified threshold, then the predicted transport status isdetermined to be not sufficiently accurate. On the other hand, if thepredicted transport status differs from the current transport status byless than the specified threshold, then the predicted transport statusis determined to be sufficiently accurate.

If the current transport status does not differ from the predictedtransport status by greater than the specified threshold, then theprocessor 105 refrains from or skips (at 206) sending a report relatingto the current transport status (referred to as a “current transportstatus report”) to the service 114 over the access network 110 at therespective time instance of the multiple time instances. Note thatrefraining from sending the current transport status report at acorresponding time instance can refer to refraining from sending acurrent transport status report at one corresponding time instance, orrefraining from sending current transport status reports at multiplecorresponding time instances. Refraining from sending the currenttransport status report allows the communication transceiver 108 to bemaintained in an inactive state (powered off or in some other lowerpower state), so that the communication transceiver 108 does not have toengage in a procedure to establish a connection with a wireless accessnetwork node to transport the application data. Alternatively, if theasset tracking device 104 is at a higher power mode, the asset trackingdevice 104 can be transitioned from the higher power mode to a lowerpower mode in response to determining that the sending of a currenttransport status report can be skipped.

However, if the current transport status differs from the predictedtransport status by greater than the specified threshold, then theprocessor 105 sends (at 208) a current transport status report to theservice 114 over the access network 110 at the the respective timeinstance of the multiple time instances.

Using techniques according to some implementations, the asset trackingdevice 104 may skip one or more scheduled current transport statusreports as long as respective one or more predicted statuses aresufficiently accurate (as explained above). As an example, if the assettracking device 104 is moving along a freeway or highway, the predictionaccuracy may be higher, which can allow for skipping of the sending ofmultiple current transport status reports. Each time an asset trackingdevice 104 skips the sending of a current transport status report at ascheduled time, asset tracking device 104 saves power consumption theasset tracking device 104 would have otherwise incurred to establish aconnection with an access network.

As the prediction algorithm improves (learns from the determination ofaccuracy of past predictions of transport statuses when compared toactual transport statuses, learns from planned route, learns fromknowledge of traffic, etc.), predicted transport statuses can becomemore accurate, such that less current transport status reports wouldhave to be sent, leading to greater savings in power consumption.

In general, solutions according to some implementations of the presentdisclosure determine one or more (up to M, M≥1) predicted locations, orpreviously predicted estimated times of arrival, or other predictedtransport statuses, of the asset tracking device 104 corresponding tothe next one or more (up to M) scheduled reporting times. The assettracking device 104 triggers the sending of a current transport statusreport only if the predicted location, previously predicted estimatedtime of arrival, or other predicted transport status deviates from acurrent location, current estimated time of arrival, or other currenttransport status by greater than a specified threshold at the scheduledreporting time.

The sending of a current status report is thus based on the accuracy ofpredicted transport status made previously. As a result, if predictedtransport statuses are accurate and the sending of a current transportstatus report is skipped, then the asset tracking device 104 canmaintain its communication transceiver 108 in an inactive state forpower savings.

If multiple metrics representing respective current transport statusesof an asset are reported, then the triggering of the sending of acurrent transport status report can be based on multiple thresholds forthe respective metrics. For instance, if at least one of the actualmeasured metrics (e.g., location, estimated time of arrival, etc.)deviates more than a specified threshold relative to a predicted valueof that metric, then the sending of a current transport status reportmay be triggered. As another example if more than a predetermined numberof actual measured metrics deviate from their predicted values by morethan their corresponding thresholds (one threshold for each metric isassumed in this case), then a current transport status report istriggered.

A specified threshold used in the comparison for triggering the sendingof a current transport status report can also be referred to as aprediction tolerance value (PTV).

The magnitude of the PTV is a system parameter which may be chosen as atradeoff between overall power consumption and accuracy of the currenttransport status reports. The PTV may be static (the same for the entirelife of use of the asset tracking device 104) or the PTV may be varieddynamically depending on the varying demand for higher or lower accuracyof tracking status information. As an example, in an area where higheraccuracy of the current status of an asset is important (e.g., areasnotorious for crime or theft, etc.), the PTV may be reduced to ensurehigher accuracy of the reported current status.

As an extension of this concept, in some examples, the PTV may be setequal to zero, meaning that a current transport status report isgenerated at each periodic instance irrespective of prediction accuracy.On the other hand, if such a high accuracy of reporting is not desired,the PTV may be increased. In the extreme case, if the next few currentstatus updates can be skipped, the PTV may be set to infinity (or a verylarge value) for these few reporting instances. The PTV may either bedetermined locally at the asset tracking device 104 or the PTV may beprovided by the service 114.

Further, the PTV may also depend on the type of asset trackingapplication. As an example, if the asset tracking application isdeployed for tracking a more sensitive (e.g., expensive) asset, the PTVcan be set to a lower value compared to an asset tracking applicationwhere a less sensitive asset is being tracked. Similarly, the PTV mayalso be used as a subscription differentiator; a lower PTV can be setfor a customer paying a higher subscription fee, or alternatively, ahigher PTV can be set for a customer paying a lower subscription fee. Tocompensate for a higher power consumption when using a lower PTV, theasset tracking device 104 may be fitted with a larger battery to providethe benefit of more accurate reporting.

1. Asset Tracking Solution Using Predicted Location Information

In the process of FIG. 2A, the asset tracking device 104 uses apredicted transport status to determine whether or not to send a reportrelating to a current transport status to the remote service 114. Inthis section (Section 1), reference is made to examples where thepredicted transport status is a predicted location of the asset trackingdevice 104 at a future time. The predicted location can be derived bythe processor 105 of the asset tracking device 104. In other examples,the predicted location can be derived by the remote service 114 insteadof by the asset tracking device 104.

In examples of this section, the current transport status is a current(actual) location determined by the asset tracking device 104.

In some implementations, the asset tracking device 104 is able topredict the location of the moveable platform 102 at a future time basedon one or more factors, including any one or some combination of thefollowing: interpolation based on a past location or multiple pastlocations of the asset tracking device 104; prediction based onknowledge of a planned route of the moveable platform 102; informationrelating to traffic and/or weather along the planned route; and soforth.

In alternative implementations, the remote service 114 can predict thelocation of the moveable platform 102 using similar factor(s) as notedabove, and the remote service 114 can transmit the predicted location tothe asset tracking device 104.

FIG. 2B is a flow diagram of an example process that can be performed bythe asset tracking device 104 according to further implementations. Theprocess of FIG. 2B can be performed by the processor 105 of the assettracking device 104.

The process of FIG. 2B includes determining (at 220) whether a currenttime is a scheduled time to send a current transport status report. Ifso, the process awakens (at 222) a GPS receiver in the asset trackingdevice 104 to acquire GPS information to determine a current location ofthe asset tracking device 104.

The process next determines (at 224) whether the current locationdiffers from a predicted location of the asset tracking device 104 bygreater than a specified distance threshold (in the form of the PTVnoted above, for example). If not, then the process skips (at 226)sending a current transport status report to the remote service 114.

However, if the current location differs from the predicted location ofthe asset tracking device 104 by greater than the specified distancethreshold, then the process activates (at 228) the communicationtransceiver 108 of the asset tracking device 104, and sends (at 230) acurrent transport status report to the remote service 114, where thecurrent transport status report includes the current location of theasset tracking device 104.

1.1 Predicted Location Information Derived by the Asset Tracking Device

In examples where predicted location information is computed by theasset tracking device 104, when the asset tracking device 104 sends areport of its current location (a current transport status report) tothe remote service 114, the asset tracking device 104 can also reportits predicted location (i.e., the location at which the asset trackingdevice 104 is likely to be located) at the next (one or more) scheduledreporting times. The number of reported predicted locations can dependon how confident the asset tracking device 104 is about the assettracking device's prediction, such as based on traffic, type of road,time of day, and so forth. If the moveable platform 102 on which theasset tracking device 104 is mounted is on a freeway or highway (with noor few traffic lights and with light or normal traffic), the assettracking device 104 can predict relatively far into the future. On theother hand, if the moveable platform 102 is on a city road withunpredictable traffic, the asset tracking device 104 may have a lowconfidence in its prediction, and as a result, the asset tracking device104 can include fewer predicted locations at future time points in areport to the remote service 114.

The asset tracking device 104 can wake up from a lower power mode to ahigher power mode at a scheduled reporting time and obtain its currentlocation (such as by using measurements of a GPS receiver, measurementsof signals from wireless access network nodes, etc.). Subsequently, theasset tracking device 104 can send a current transport status report ifthe obtained current location (at the scheduled reporting time) differsfrom the predicted location (for the scheduled reporting time) bygreater than the specified threshold. The specified threshold can be adistance threshold that can be tailored to a given application or goal.For example, the distance threshold can be set lower to provide improvedaccuracy in reporting the location of the asset (more current transportstatus reports are sent but this comes at the expense of higherconsumption), and can be set higher to reduce battery consumption (lesscurrent transport status reports are sent).

In some examples, when the asset tracking device 104 sends a currenttransport status report at a scheduled reporting time, in response tothe current location exceeding the predicted location by greater thanthe distance threshold, the asset tracking device 104 can also send pastlocations of the asset tracking device 104 at times where sending ofreports was skipped. Sending such past locations can help the remoteservice 114 to update predicted locations to a more accurate level ofconfidence.

In some examples, the client device 116 (FIG. 1) that is communicativelycoupled to the service 114 can present a graphical user interface (GUI)visualization, to allow a user of the client device 116 to accessinformation stored by the service 114. Such information stored by theservice 114 can include locations of assets at corresponding times. Theclient device 116 can plot locations of assets, and possibly also canplot predicted locations of assets, in the GUI visualization. In someexamples, actual locations can be represented with icons of a firstrepresentation such as a first color, while predicted locations can berepresented with icons of a second representations such as a secondcolor in the GUI visualization. When an actual location is obtained in asubsequent report, the GUI visualization can replace a predictedlocation with an actual location, and the corresponding representation(e.g. the color) of the icon can be replaced or updated accordingly.

FIG. 3 shows an example where the moveable platform 102 travels along aroad 302 (from right to left in the figure). In FIG. 3, each solidrectangular box (304-0, 304-1, 304-2, 304-3, and 304-4) represents anactual location of the moveable platform 102, and each dashed box(306-1, 306-2, 306-3, and 306-4) represents a predicted location. Icons308 and 310 represent traffic incidents along the road 302 that wereunknown at the time (T0) that an initial current transport status report(Report 0) was sent by the asset tracking device 104 to the service 114using a wireless access network node 310-0. FIG. 3 further showsadditional wireless access network nodes 310-1, 310-2, 310-3, and 310-4that can be used by the asset tracking device 104 to send currenttransport status reports (if triggered) to the remote service 114.

Report 0 includes the current location at time T0 (the time Report 0 issent), as well as M predicted locations at M corresponding future timepoints, where M≥1. In the example of FIG. 3, M=4, so that Report 0includes 4 predicted locations at 4 corresponding future time points.

In FIG. 3, at time T1, the asset tracking device 104 compares the actuallocation 304-1 to the predicted location 306-1 for time T1, anddetermines that the actual location 304-1 does not differ from thepredicted location 306-1 by greater than the specified distancethreshold. As a result, the sending of Report 1 at time T1 is skipped.

At time T2, the asset tracking device 104 compares the actual location304-2 to the predicted location 306-2 for time T2, and determines thatthe actual location 304-2 does not differ from the predicted location306-2 by greater than the specified distance threshold. As a result, thesending of Report 2 at time T2 is skipped.

As a result of a traffic incident (308), the moveable platform 102 isdelayed. Consequently, at time T3, the asset tracking device 104determines that the actual location 304-3 differs from the predictedlocation 306-3 for time T3 by greater than the specified distancethreshold. In response, the asset tracking device 104 should send Report3 at time T3. However, in the example of FIG. 3, the asset trackingdevice 104 does not have a connection to the wireless access networknode 310-3 (either because the asset tracking device 104 is outside thecoverage area of the wireless access network node 310-3, or the assettracking device 104 has lost its connection to the wireless accessnetwork node 310 for some other reason). Without a connection to thewireless access network node 310-3, the asset tracking device 104 skipsthe sending of Report 3. However, the asset tracking device may keepsearching for a communication network in this case.

Later, at time T4, when the asset tracking device 104 has acquired anetwork coverage and hence the connection to the wireless access networknode 310-4, the asset tracking device 104 sends Report 4 to the remoteservice 114. The sending of Report 4 can occur based on the fact thatthe sending of Report 3 was skipped due to lack of coverage.

Moreover, as shown in the example of FIG. 3, due to another trafficincident (310), the moveable platform 102 is delayed even further.Consequently, at time T4, the asset tracking device 104 determines thatthe actual location 304-4 differs from the predicted location 306-4 fortime T4 by greater than the specified distance threshold, which wouldhave triggered the sending of Report 4 anyway.

Even though the asset tracking device 104 does not have a connection tothe wireless access network node 310-3 at a location when the scheduledcurrent transport status report is to be sent (e.g., Report 3 in FIG.3), the service 114 still has a predicted location (from Report 0)available until the asset tracking device 104 sends the next currenttransport status report. When the service 114 sends asset trackinginformation to the client device 116 (FIG. 1), the service 114 may tag alocation information either as a predicted location information or anactual location information.

In some examples according to the present disclosure, if the assettracking device 104 does not have a network connection at a locationwhere a current transport status report is triggered, and if thedifference between the predicted and actual locations is greater thanthe specified distance threshold, then the asset tracking device 104stays awake to send a current transport status report as soon as thenetwork connection is re-established.

In some examples, the specified distance threshold may be static.Alternatively, the specified distance threshold may vary over time basedon one or more factors, such as the actual location, a battery level,and so forth. The following are examples of how the specified distancethreshold can be varied:

-   -   If the battery level is low, increase the threshold to reduce        the number of current transport status reports and increase        power savings. If the battery level is high, the threshold can        be decreased to increase the number of current transport status        reports.    -   If the actual location indicates that the moveable platform 102        is in a geographic area that is known to be safe (less        occurrences of theft), then the threshold can be increased to        save battery. If the actual location indicates that the moveable        platform 102 is in a high theft area, then the threshold can be        decreased to trigger a larger number of current transport status        reports. Thus, the threshold can be based on a safety status of        a location, where the safety status can refer to a likelihood of        theft or loss of the asset.    -   The threshold can vary as a function of whether or not the asset        tracking device 104 is in network coverage. If there is a        relatively high expectation or probability that the asset        tracking device 104 may be out of coverage at one or more        predicted locations, a larger threshold value may be set to        avoid awakening the asset tracking device 104 in a location of        no coverage and performing network searching). Once the asset        tracking device 104 is back in coverage, the asset tracking        device 104 will report the actual location.    -   Note that increasing the threshold means that there is slightly        more uncertainty in the predicted location. However, location        information (e.g., predicted location information) is still        available to client devices accessing the service 114.    -   The threshold can be varied based on application or use case.    -   The threshold can be varied based on actual proximity to the        destination. For example, more accuracy in location information        may be desirable the closer the asset tracking device 104 is to        the destination.    -   The threshold can be varied based on estimated time of arrival        or proximity to a destination. For example, less accuracy can be        tolerated when the estimated time of arrival is 10 hours in the        future versus when the estimated time of arrival is half an hour        in the future.    -   The threshold can be varied based on expected average speed at        the predicted location. For example, if the moveable platform        102 is on a freeway, the tolerance can be set higher than when        the moveable platform 102 is on a city road.    -   The threshold can be varied based on the number of skipped        current transport status reports.

1.2 Predicted Location Information Derived by the Remote Service

In Section 1.1 above, reference is made to predicted locationinformation derived by the asset tracking device 104. In this section(Section 1.2), examples are described where the predicted locationinformation is derived by the remote service 114 and sent by the service114 to the asset tracking device 104.

More generally, instead of using the asset tracking device 104 topredict a transport status, the service 114 can be used to compute thepredicted transport status.

In this solution, the asset tracking device 104 triggers the sending ofan initial report (e.g., Report 0 in FIG. 3). However, unlike thesolution in Section 1.1, in this case, the service 114 does theprediction and may, in response to the location report from the assettracking device 104, or independently, generate and transmit one or morepredicted locations (at the next few scheduled reporting times). Theservice 114 may also indicate one or more specified thresholds to usefor determining whether or not to trigger the sending of a scheduledcurrent transport status report.

The process run at the asset tracking device 104 to generate nextcurrent transport status reports is then similar to the processdescribed in Section 1.1.

Some example benefits of performing location prediction (or othertransport status prediction) at the service 114 rather than at the assettracking device 104 can include the following:

-   -   The prediction process is performed centrally at the service 114        and can be upgraded or modified (without updating the program        code on asset tracking devices.    -   The service 114 can leverage more information (e.g., traffic        information, etc.) to predict locations or other transport        statuses, as the service 114 may have more ready access to        sources of such information, as compared to the asset tracking        device 104 itself.    -   Running the prediction process and information retrieval at the        asset tracking device 104 may result in additional power        consumption, whereas if the prediction process and information        retrieval were obtained at the service 114, the asset tracking        device 104 would not have to perform such tasks.

1.3 Generating a Predicted Location

In some examples, a predicting entity (either the asset tracking device104 or the service 114) can use the asset tracking device's currentactual location determined at a reporting time to generate predictedlocation(s) corresponding to the next (M) reporting instance(s). Thepredicting entity can generate a periodic report every N minutes. Thus,at the time of any given current transport status report, the predictingentity knows when the next current transport status report will betriggered. Based on this, and by using the knowledge of the currentlocation of the asset tracking device, it is possible for the predictingentity to predict a future location(s) at which the asset trackingdevice 104 is likely to be at the time of the next reportinginstance(s). In general, one or more of the following factors may beused by the predicting entity to generate a predicted locationcorresponding to a future reporting instance:

-   -   The time at which the future report will be generated.    -   The current location (i.e., location at the time of generating        the prediction).    -   Past location history (this may include locations at which the        asset tracking device 104 was in the past including the        locations at the time of past reporting instances).    -   Knowledge of a planned route or route information.    -   Knowledge of traffic incidents or traffic volume that may impact        the predicted location.    -   Knowledge of vehicle speed and direction of travel.    -   Weather and other factors that may affect the future location at        the time of next report.

In other examples, further or alternative factors may be considered.

The task of generating the predicted location can be performed using anyof a number of prediction techniques, such as a linear extrapolation orsome other non-linear techniques that exploit the associated uncertaintywith any specific location information used in the prediction algorithmsuch as Kalman filtering.

It should be noted that more than one predicted location can begenerated at any given time. For instance, up to M predicted locationscorresponding to future M periodic reporting times may be generated at agiven point in time. It should be noted that a predicted location may ormay not be accurate (i.e., may deviate from the actual location by morethan a specified threshold) depending on various conditions. Further, apredicted location corresponding to a reporting time that is furtherinto the future may be less accurate than a predicted locationcorresponding to a reporting time that is closer to the current time.

As the number of predicted locations increase, the likelihood of apredicted location deviating from an actual location by more than aspecified threshold will also increase progressively.

The number M of predicted locations that are computed and reported canbe chosen based on a tradeoff between power consumption and accuracy ofreports. Thus, similar considerations apply to the value of M as thoseapplicable for choosing the value of a specified threshold (e.g., aPTV). The value of M may be varied dynamically depending on varyingdemands for higher or lower accuracy of location information. As anexample, in an area where higher accuracy of location reporting isimportant (e.g., areas notorious for crime or theft), the value of M maybe reduced to ensure higher location prediction accuracy (and to ensurethat more frequent current transport status reports are transmitted). Insome examples, M may be set to 0, which means that a current transportstatus report is generated at each scheduled reporting time. On theother hand, if such a high accuracy of reporting is not desired, M maybe increased in value. The value of the M may either be determinedlocally at the asset tracking device 104 or at the remote service 114(which can then send the value of M to the asset tracking device 104).

Further, the value of M may also depend on the type of asset trackingapplication. As an example. if the asset tracking application isdeployed for tracking a more sensitive (e.g., expensive) asset, thevalue of M can be set to a lower value compared to an asset trackingapplication where a less sensitive asset is being tracked. Similarly,the value of M may also be used as subscription differentiator. Forexample, a lower value of M is set for a customer paying a highersubscription fee, while a higher value of M is set for a customer payinga lower subscription fee. To compensate for higher power consumptionwhen using a lower M value, the asset tracking device 104 may be fittedwith a larger battery.

2. Asset Tracking Solution Using Estimated Time of Arrival

In some use cases, it may not be important for an entity that tracksassets to know exactly where an asset (or a moveable platform carryingthe asset) is. Rather, the entity may wish to know about the estimatedtime of arrival of the asset, so that, for example, a loading bay in awarehouse can be allocated and prepared in advance of the arrival of themoveable platform carrying the asset.

As an alternative or in addition to providing periodic locationinformation (actual location information and/or predicted locationinformation), the entity can be provided with the current estimated timeof arrival (ETA). In some examples, a user can use the client device 116(FIG. 1) to select the type(s) of transport status that the assettracking device 114 should report. For example, the client device 116can have a GUI screen that allows the user to select reporting of anyone or more of the following by the asset tracking device 104: locationinformation, estimated time of arrival, or other transport statusinformation.

FIG. 4 illustrates an example process that can be performed by the assettracking device 104 for reporting estimated times of arrival. When themoveable platform 102 starts or resumes its journey (e.g., starts movingafter a period of being stationary), the asset tracking device provides(at 402) an estimated time of arrival to the service 114. This providedestimated time of arrival can be referred to as Last_Provided_ETA.

The estimated time of arrival that is provided can be computed by theasset tracking device 104 based on any one or some combination of thefollowing factors: the moveable platform's current location, themoveable platform's current speed, information of a route and speedrestrictions along the route, information regarding traffic orcongestion on the route, information of weather conditions, informationindicating restrictions on operation of the moveable platform (e.g.,regulated maximum speed), and so forth.

The asset tracking device 104 also obtains an ETA threshold, which is anexample of the specified threshold used in task 206 of FIG. 2A. Theasset tracking device 104 can determine the ETA threshold, oralternatively, the asset tracking device 104 can receive the ETAthreshold from the service 114. The ETA threshold can be varied based onone or more factors, such as based on an application, a use case, and soforth. The ETA threshold can be measured in time units, and defines theacceptable inaccuracy in estimated time of arrival prediction. An ETAthreshold of ±10 minutes would mean that the estimated time of arrivalthat is reported is the estimated time of arrival plus or minus 10minutes.

Next, the asset tracking device 104 determines (at 403) if a trigger tocompute a new current estimated time of arrival (referred to as New_ETA)has occurred. For example, the New_ETA can be computed at a nextscheduled time (periodic time or other scheduled time), at a specificlocation, on reception of information concerning road traffic congestionor worsening weather, or in response to any other trigger. If so, theasset tracking device 104 computes (at 404) the New_ETA.

The asset tracking device 104 determines (at 406) if the New_ETA differsfrom the Last_Provided_ETA by greater than the ETA threshold. If not,then the asset tracking device 104 refrains (at 408) from sending acurrent transport status report to the service 114.

However, if the New_ETA differs from the Last_Provided_ETA by greaterthan the ETA threshold, then the asset tracking device 104 sends (at410) a current transport status report to the service 114, where thecurrent transport status report includes the New_ETA as the providedestimated time arrival (Last_Provided_ETA to be used in the nextiteration) of FIG. 4. The asset tracking device 104 then sets (at 412)Last_Provided_ETA equal to New_ETA.

A new ETA threshold may optionally be obtained at this point, e.g., asprovided from the service 114 to the asset tracking device 104.

The process then returns to task 403 to iterate through tasks 403-412.

In alternative examples, an asymmetric ETA threshold can be used, wherethe asymmetric ETA threshold can be in the form of +M/−N time units,where M is different from N. In other words, the asset tracking device104 triggers the sending of a current transport status report inresponse to New_ETA being greater than +M time units thanLast_Provided_ETA, or in response to New_ETA being −N time units lessthan Last_Provided_ETA. In some examples, the use of an asymmetric ETAthreshold may be useful if a warehouse manager or other entity does notcare if the cargo arrives early (within some bound), but definitelywants to know if the cargo is going to arrive late (or vice versa).

In further examples, the ETA threshold can be set to be a dynamicallydecreasing function of the estimated time of arrival. For example, ifthe estimated time of arrival is 10 hours (or some other large timeduration) in the future, then an ETA threshold of 1 hour may be adequate(from the perspective of an entity that is seeking the asset transportstatus). However, if the estimated time of arrival is 1 hour (or someother small time duration) in the future, then a smaller ETA threshold(e.g., 10 minutes) may be used to trigger more current status reports.

3. Aspects Related to Skipped Report

As explained above, a reduction in power consumption at the assettracking device 104 can be accomplished by skipping the sending ofcurrent status reports when an actual current transport status isreasonably close in value to a predicted current transport status.

At any given time, the service 114 can have one or more of the followingtypes of transport status information:

-   -   1. Actual transport status information in received current        status reports sent by the asset tracking device 104. The actual        transport status information is not predicted transport status        information.    -   2. Predicted transport status information, which can be one of        the following sub-types:        -   a. A predicted transport status information corresponding to            a past time instance. This past predicted transport status            information can correspond to a reporting time where the            sending of a current status report was skipped by the asset            tracking device 104.        -   b. A predicted transport status information corresponding to            a future time instance. This future transport status            information corresponds to reporting time that is in the            future. The asset tracking device 104 may later transmit an            actual transport status in a report at that reporting time            (e.g., if the actual transport status differs from the            predicted transport status by more than the specified            threshold).

FIG. 5 shows an example of a GUI visualization 500 that can be displayedbased on information from the service 114. The GUI visualization 500 canbe displayed at the client device 116, for example. The GUIvisualization 500 includes a geographic map that shows a road 502 alongwhich the moveable platform 102 is traveling.

The GUI visualization 500 shows an example where the displayed transportstatus information is location information (actual location informationor predicted location information). When displaying locationinformation, the service 114 may distinguish between the different typesof location information in the displayed GUI visualization 500.

The GUI visualization 500 shows four locations 504, 506, 508, and 510 ofan asset that is being tracked. The locations 504, 506, 508, and 510 areplotted as truck icons along the road 502 in the displayed map. Thelocation 504 is an actual location (for time 14:00) received in acurrent status report from the asset tracking device 104. The locations506, 508, and 510 are predicted locations for future time points,including 14:15, 14:30, and 14:45. Each predicted location 506, 508, or510 is associated with a corresponding visible representation ofuncertainty (e.g., in form of an uncertainty circle 512, 514, or 516,respectively, drawn around the respective predicted location.

In other examples, an uncertainty bar may be displayed instead of acircle for each predicted location. The size or length of theuncertainty bar can represent the respective amount of uncertaintyassociated with a predicted location displayed in the GUI visualization500.

The radius of each circle 512, 514, or 516 can represent the expecteduncertainty in the prediction. The radius of the circle 512 is 0.5kilometers (km), the radius of the circle 514 is 0.7 km, and the radiusof the circle 516 is 0.8 km. A larger circle indicates greateruncertainty in the respective predicted location. Note that if the routeis known, the uncertainty of the location is along the known route(e.g., the road 502 shown in FIG. 5).

Assuming that the current time is between 14:15 and 14:30, then thepredicted location 506 can be one where the sending of a current statusreport was skipped by the asset tracking device 104, such as due to acurrent location not differing from the corresponding predicted location(for time 14:15) by greater than a specified distance threshold. On theother hand, if the current time is between 14:15 and 14:30, thenpredicted locations 508 and 510 are future predicted locations for whichcurrent status reports are not yet due. In some examples, predictedlocations displayed in the GUI visualization 500 associated with skippedreports can be displayed in a first representation, such as a firstcolor, while predicted locations displayed in the GUI visualization 500associated with future time points can be displayed in a secondrepresentation, such as a second color different from the first color.In other examples, other different visual indications can be used todistinguish between displayed predicted locations for which currentstatus reports have been skipped and displayed predicted locations forfuture time points.

There can be a direct correspondence between the specified threshold(e.g., the PTV noted above) and the resulting uncertainty in thepredicted location of an asset. The radius of an uncertainty circle canbe set based on the corresponding specified threshold value, oralternatively, the length of an uncertainty bar may be based on thecorresponding specified threshold value.

Note that the uncertainty can increase as a function of the number ofskipped reports since the last report of actual location, so that thesize of displayed uncertainty circles may gradually increase withincreasing time into the future.

Failure to receive a current status report may be due to one of severalreasons. A first reason is that the difference between predicted andactual locations is less than the specified threshold, which caused theasset tracking device 104 to skip the sending of the correspondingcurrent status report. A second reason is that the difference betweenpredicted and the actual locations is greater than the specifiedthreshold, but a current status report has not yet been transmitted(e.g., due to lack of network connection) or a transmitted currentstatus report was not successfully received at the service 114 (e.g.,due to errors over the transmission medium, etc.).

In the case of lack of network connection or failure of successfulcommunication (the second reason above), even though the service 114 maynot have received actual current locations, the service 114 may stillhave predicted locations, which may be displayed to the user.

Since the service 114 also knows that a reporting time has passed, theservice 114 knows that a corresponding report may have been skipped. Ifthe service 114 also knows that wireless access network coverage existsat this location, the service 114 may conclude with a greater degree ofcertainty that a report has indeed been skipped. This greater degree ofcertainty can be indicated using a representation, such as a differentcolor. As noted above, the service 114 can display predicted locationsassociated with skipped reports differently than predicted locations forfuture time points.

At the asset tracking device 104, the operation of the asset trackingdevice 104 differs depending on which of the first and second reasonsabove caused the skipping of a current status report. In the scenariowhere the first reason caused the skipping of a current status report,the asset tracking device 104 can maintain its communication transceiver108 in an inactive state, and activates the communication transceiver108 only at the next scheduled reporting time. However, in the scenariowhere the second reason caused the skipping of a current status report,the asset tracking device 104 can keep the communication transceiver 108active, and can keep searching for a wireless access network until thecommunication transceiver 108 establishes a connection with a wirelessaccess network. As soon as the communication transceiver 108 establishesa connection with a wireless access network, a new current status reportcan be transmitted by the asset tracking device 104.

Further, even when a report is skipped due to the difference betweenactual location and predicted location being less than the specifiedthreshold, the asset tracking device 104 may still log the actuallocation information locally in the asset tracking device 104 (i.e.,although this information is not reported to the service 114, thelocation information is not lost). Actual location informationcorresponding to skipped report(s) can then be transmitted eventually tothe service 114 when a subsequent location report is transmitted.

Upon eventually receiving a current status report from the assettracking device 104, the service 114 can refresh displayed locations(such as in the GUI visualization 500) using information in the receivedcurrent status report. For example, predicted locations can be replacedwith updated locations, and the corresponding visual indications can beupdated accordingly in the GUI visualization 500.

Moreover, predicted locations displayed in the GUI visualization 500 canalso be updated, either based on predicted locations included in areceived current status report, or based on updated predictions made bythe service 114 in response to receiving a current status report.

4. Signaling Between an Asset Tracking Device and a Service

In some examples, as shown in FIG. 6, when the asset tracking device 104sends (at 602) a current status report to the service 114, the assettracking device 104 can include the actual current transport status aswell as up to M (M≥1) predicted transport statuses, in examples wherethe determination of predicted transport statuses is performed by theasset tracking device 104.

As further shown in FIG. 6, the service 114 responds to the currentstatus report by sending (at 604) an acknowledgement (ACK) message aswell as prediction assistance information to be used by the assettracking device 104 to predict transport statuses. The predictionassistance information sent by the service 114 can include a value of M,a specified threshold (e.g., the PTV), and so forth. Sending theprediction assistance information with or as part of the acknowledgmentmessage allows for more efficient usage of the communication transceiver108 of the asset tracking device 104, since the communicationtransceiver 108 does not have to be separately activated to receive theacknowledgment and the prediction assistance information.

Although FIG. 6 shows the service 114 sending prediction assistanceinformation with an acknowledgment message that is responsive to acurrent status report, it is noted that in other examples, theprediction assistance information can be separately sent by the service114 to the asset tracking device 104, which may have occurred in thepast. The prediction assistance information can be static, so that it isreported just once by the service 114. In other examples, the predictionassistance information can be dynamic and can be reported by the service114 to the asset tracking device 104 multiple times.

In other examples, instead of receiving the value of M and/or PTV fromthe service 114, the asset tracking device 104 can locally determine thevalue of M and/or PTV.

FIG. 6 shows an example where the predicted transport statuses arecomputed by the asset tracking device 104 and sent in a current statusreport to the service 114. In alternative examples, the computation ofpredicted transport statuses is performed by the service 114.

A benefit of generating predicted transport statuses at the service 114is that the information that is useful for generating the prediction maybe obtained more easily by the service 114 than by the asset trackingdevice 104. As an example, obtaining information such as traffic and/orweather conditions may be performed without any additional power penaltyto the asset tracking device 104 if the prediction is done at theservice 114 (this is because the service 114 is located at a centrallocation that has continual access to a network connected to varioussources of information.

FIG. 7 shows an example where predicted transport statuses are generatedby the service 114. In response to receiving (at 702) a current statusreport (containing an actual current transport status) from the assettracking device 104, the service 114 responds by generating one or more(up to M) predicted transport statuses, and sends (at 704) the Mpredicted transport status(es) to the asset tracking device 104 (alongwith or as part of an acknowledgment message, ACK, responsive to thecurrent status report). The service 114 can also send PTVs correspondingto the M predicted transport statuses (one PTV per predicted transportstatus, where in some examples the PTV for a first predicted transportstatus can differ from the PTV for a second predicted transport status).

As an alternative, the PTVs may be generated by the asset trackingdevice 104 locally.

The generation of a predicted transport status can be based on one orsome combination of the following factors: a time at which a currentstatus report is to be sent, a transport status at a time when thepredicted transport status is generated, a prior transport status of theasset, a location of the moveable platform, a planned route of theasset, a speed restriction along the planned route, information oftraffic along the planned route, a speed of the moveable platform, arestriction on a speed of the moveable platform, a direction of travelof the moveable platform, and weather information.

5. System Architecture

FIG. 8 shows an example of a system 800, which can be implemented with acomputer or multiple computers. The system 800 can be used to implementthe service 114 discussed above. The system 800 includes a processor (ormultiple processors) 802. In addition, the system 800 includes acommunication transceiver 804 to communicate over a network, and anon-transitory machine-readable or computer-readable storage medium 806that stores machine-readable instructions 808, such as asset trackingservice instructions of the service 114, for execution on theprocessor(s) 802 to perform the tasks of the service 114 discussedherein.

The storage medium 806 can any or some combination of the following: asemiconductor memory device such as a dynamic or static random accessmemory (a DRAM or SRAM), an erasable and programmable read-only memory(EPROM), an electrically erasable and programmable read-only memory(EEPROM) and flash memory; a magnetic disk such as a fixed, floppy andremovable disk; another magnetic medium including tape; an opticalmedium such as a compact disk (CD) or a digital video disk (DVD); oranother type of storage device. Note that the instructions discussedabove can be provided on one computer-readable or machine-readablestorage medium, or alternatively, can be provided on multiplecomputer-readable or machine-readable storage media distributed in alarge system having possibly plural nodes. Such computer-readable ormachine-readable storage medium or media is (are) considered to be partof an article (or article of manufacture). An article or article ofmanufacture can refer to any manufactured single component or multiplecomponents. The storage medium or media can be located either in themachine running the machine-readable instructions, or located at aremote site from which machine-readable instructions can be downloadedover a network for execution.

In the foregoing description, numerous details are set forth to providean understanding of the subject disclosed herein. However,implementations may be practiced without some of these details. Otherimplementations may include modifications and variations from thedetails discussed above. It is intended that the appended claims coversuch modifications and variations.

What is claimed is:
 1. A device comprising: a battery; and a processorpowered by the battery and configured to: compare a current transportstatus of an asset to a predicted transport status of the asset at eachrespective time instance of a plurality of time instances, wherein thecurrent transport status includes a current expected time of arrival ofthe asset, and the predicted transport status includes a previouslypredicted expected time of arrival of the asset; in response todetermining, based on the comparing, that the current expected time ofarrival of the asset does not differ from the previously predictedexpected time of arrival of the asset by greater than a specifiedthreshold: skip sending a report relating to the current transportstatus to a service over a network at the respective time instance ofthe plurality of time instances, and transition the device from a higherpower mode to a lower power mode for power saving.
 2. The device ofclaim 1, wherein each of the current transport status and the predictedtransport status is represented by one or more metrics.
 3. The device ofclaim 1, wherein the processor is configured to: in response todetermining that the current expected time of arrival differs from thepreviously predicted expected time of arrival by greater than thespecified threshold: detect that the device is out of network coverage,in response to detecting that the device is out of network coverage,maintain a communication transceiver of the device active to wait foravailability of the network coverage, wherein the sending of the reportis responsive to detecting the availability of the network coverage. 4.The device of claim 1, wherein the specified threshold is variable overtime based on one or more factors selected from among: a level of thebattery, a safety status of a region where the device is located, and anexpected availability of network coverage for the device.
 5. The deviceof claim 1, wherein the processor is configured to further: receive,over the network, the specified threshold that is set based on atradeoff between accuracy of reporting of a transport status of theasset and power saving at the device.
 6. A device comprising: a battery;and a processor powered by the battery and configured to: compare acurrent transport status of an asset to a predicted transport status ofthe asset at each respective time instance of a plurality of timeinstances; in response to determining that the current transport statusdoes not differ from the predicted transport status by greater than aspecified threshold: skip sending a report relating to the currenttransport status to a service over a network at the respective timeinstance of the plurality of time instances, and transition the devicefrom a higher power mode to a lower power mode for power saving; andreceive, over the network, the specified threshold that is set based ona tradeoff between accuracy of reporting of a transport status of theasset and power saving at the device.
 7. The device of claim 6, whereinthe current transport status includes a current location of the asset,and the predicted transport status includes a predicted location of theasset, wherein the processor is configured to: in response todetermining, based on the comparing, that the current location of theasset does not differ from the predicted location of the asset bygreater than the specified threshold, perform the skipping and thetransitioning.
 8. The device of claim 7, wherein the processor isconfigured to: in response to determining that the current location ofthe asset differs from the predicted location of the asset by greaterthan the specified threshold, transition the device from the lower powermode to the higher power mode, and send a report relating to the currentlocation of the asset to the service over the network.
 9. The device ofclaim 8, wherein the report relating to the current location of theasset includes the current location of the asset.
 10. The device ofclaim 6, wherein the processor is configured to calculate the predictedtransport status.
 11. The device of claim 10, wherein the processor isconfigured to calculate a configurable number of predicted transportstatuses, the configurable number variable as a function of one or morefactors.
 12. The device of claim 6, wherein the processor is configuredto receive, over the network, the predicted transport status calculatedby the service.
 13. The device of claim 6, wherein the predictedtransport status is calculated based on one or more of: a time at whichthe report relating to the current transport status is to be sent, atransport status at a time when the predicted transport status isgenerated, a prior transport status of the asset, a location of amoveable platform carrying the asset, a planned route of the asset, aspeed restriction along the planned route, information of traffic alongthe planned route, a speed of the moveable platform, a restriction on aspeed of the moveable platform, a direction of travel of the moveableplatform, and weather information.
 14. A non-transitory machine-readablestorage medium storing instructions that upon execution cause a deviceto: at each respective time instance of a plurality of time instances,awaken the device to compare a current transport status of an asset to apredicted transport status of the asset; in response to determining thatthe current transport status does not differ from the predictedtransport status by greater than a specified threshold at the respectivetime instance, refrain from sending a report relating to the currenttransport status to a service over a network at the respective timeinstance, and maintain a communication transceiver of the device in aninactive state; in response to determining that the current transportstatus differs from the predicted transport status by greater than thespecified threshold at the respective time instance, activate thecommunication transceiver to send a report relating to the currenttransport status to the service over the network at the respective timeinstance; and compute the specified threshold based on a battery levelby increasing the specified threshold based on detecting a reducedbattery level of a battery.
 15. The non-transitory machine-readablestorage medium of claim 14, wherein the instructions upon executioncause the device to: in response to determining that the currenttransport status does not differ from the predicted transport status bygreater than the specified threshold at the respective time instance,transition the device from a higher power mode to a lower power mode forpower saving; and in response to determining that the current transportstatus differs from the predicted transport status by greater than thespecified threshold at the respective time instance, transition thedevice from the lower power mode to the higher power mode.
 16. Thenon-transitory machine-readable storage medium of claim 14, wherein thecurrent transport status includes a current expected time of arrival ofthe asset, and the predicted transport status includes a previouslypredicted expected time of arrival of the asset, wherein theinstructions upon execution cause the device to: in response todetermining that the current expected time of arrival of the asset doesnot differ from the previously predicted expected time of arrival of theasset by greater than the specified threshold, perform the refrainingand the maintaining.